1. Field of the Invention
The present invention relates to a method aimed at optimizing the architecture of a mobile terminal supporting a location function based on receiving signals from a global navigation satellite system (GNSS) and wireless communication using orthogonal frequency diversity multiplexing (OFDM), such as a WiFi™ function conforming to the 802.11a or 802.11g standard or supporting a WiFi™ function by means of a dual-band chip conforming to a standard that is not compatible with OFDM coding and also to a standard that is compatible therewith.
2. Description of the Prior Art
In a satellite positioning system using radio navigation satellite system (RNSS) terminals such as a Global Positioning System (GPS) or GLONASS terminal, the data signals for calculating the position of the terminal come from different satellites (at least four satellites in order to determine four unknowns x, y, z and t).
The GPS signal broadcast by each satellite is based on a spread spectrum technique. The signal is therefore a binary data signal modulated by a signal whose spectrum has been spread by a code division multiple access (CDMA) method. In other words, each bit of the data signal is replaced by a spreading sequence specific to each satellite. The data is transmitted serially at 50 bit/s (equivalent to 0.02 s/bit). A spreading sequence such as a Gold pseudorandom sequence is transmitted at a much higher rate; a Gold sequence can be considered as a series of bits with a clearly defined clock period; the term “code moment” (or the more frequently used term “chip”) refers to a bit of the sequence and, by extension, to the duration of this kind of bit. The spreading sequence is transmitted at a rate of 1.023 Mchip/s (a chip therefore has a duration of approximately 1 μs) and comprises 1023 chips (having a duration of 1 ms); there are therefore 20 sequence repetitions per data bit.
Modulation by the signal whose spectrum has been spread means that a “normal” demodulator will interpret the received signal as noise.
To separate the signals coming from different satellites, the terminal correlates the signal received and a local replica of the spreading code corresponding to the satellite whereof the information content is to be extracted.
Generally speaking, the correlation function f(τ) of two signals fi(t) and fj(t) is given by the equation:
      f    ⁡          (      τ      )        =            ∫              +        ∞                    -        ∞              ⁢                            f          i                ⁡                  (          t          )                    ·                        f          j                ⁡                  (                      t            -            τ                    )                    ·                          ⁢              ⅆ        t            
in which τ designates a variable time. Of course, in practice, the integration is not performed from −∞ to +∞, but over a finite time period, dividing the integral by the duration of said period. If the functions fi(t) and fj(t) are identical, the term autocorrelation function is used; if the functions fi(t) and fj(t) are different, the term intercorrelation function is used.
Each satellite k has its own pseudorandom signal ck(t). Each of these pseudorandom signals has the property that its autocorrelation function is a null function except in the vicinity of the null time shift, where it assumes a triangular shape. In other words, the integral
      ∫          +      ∞              -      ∞        ⁢                    c        k            ⁡              (        t        )              ·                  c        k            ⁡              (                  t          -          τ                )              ·                  ⁢          ⅆ      t      has a null value when τ has a non-null value and is at a maximum when τ has a null value.
Furthermore, the signals each associated with a different satellite are selected so that they have a null intercorrelation function; in other words, the integral
      ∫          +      ∞              -      ∞        ⁢                    c        k            ⁡              (        t        )              ·                  c        k        ′            ⁡              (                  t          -          τ                )              ·                  ⁢          ⅆ      t      has a null value when τ has any value if k and k′ are different.
The signals from the satellites whose spectra have been spread are therefore chosen to be orthogonal.
When the terminal is seeking to acquire data from a particular satellite, it correlates the signal received with a replica of the pseudorandom sequence of the satellite concerned (this sequence is assigned to the satellite once and for all and does not change during the lifetime of the satellite).
Accordingly, the signal S(t) received by the terminal is the sum of all of the signals transmitted by each satellite:
            S      ⁡              (        t        )              =                  ∑                  k          =          1                n            ⁢                                    c            k                    ⁡                      (            t            )                          ·                              d            k                    ⁡                      (            t            )                                ,where n is the number of satellites, ck(t) represents the spread spectrum signal from the satellite k and dk(t) represents the data from the satellite k.
To acquire the data from the satellite m, the local replica corresponds to the signal cm(t). Accordingly, following correlation, and assuming that the spreading signals are perfectly orthogonal, all the data from the satellites that are not being looked for (the intercorrelation functions whereof have a null value) are eliminated, leaving only the data from the satellite m. Correlation is possible because the duration of a spreading sequence is twenty times smaller than the duration of a data bit.
The signal acquisition phase consists in calculating the correlation of the signal received with the local replica of the required satellite code over a time period equivalent to the period of the code, which is 1 ms, with a depth (integral limit) depending on the detection performance required.
However, implementing this kind of solution gives rise to certain difficulties, in particular in terms of calculation complexity.
The most widely used and effective technique for reducing the computation load computes the correlation function using fast Fourier transforms. The computation steps are then as follows:                compute the Fourier transform of the incoming signal on a given time support,        compute the fast Fourier transform of the local replica of the spreading code corresponding to the satellites whose information is to be extracted,        multiply the resulting two vectors,        compute the inverse fast Fourier transform of the product.        
Although this computation method achieves a significant improvement in terms of computation complexity, it is nevertheless very costly to implement in terminals with limited capacity in terms of computation power and power consumption. This is precisely the situation in a mobile terminal such as a mobile telephone.
Also, communication techniques based on OFDM modulation techniques are expanding at an increasing rate. For example, the 802.11a and 802.11g WiFi™ techniques are based on OFDM modulation.
The OFDM modulation technique is based on a technique of optimum frequency diversity obtained by fast Fourier transform computation on the modulating signal. Details of this technique can be found in the thesis “The suitability of OFDM as a modulation technique for wireless telecommunications, with a CDMA comparison”, Eric Lawrey, October 1997. This modulation technique employs a large number of fast Fourier transform calculations. To this end, mobile communication terminal manufacturers are developing dedicated computation devices, thereby increasing the complexity of the architecture of these mobile terminals and their power consumption.
The invention starts with the astute observation that GNSS and OFDM computation techniques are very similar, the invention therefore consists in judiciously pooling resources to optimize the architecture of mobile terminals supporting a satellite location function and a wireless communication function based on OFDM modulation.